Federal Railroad Administration

Cooperative strategies of individuals within a distributed organization can contribute to increased efficiency of operations and safety. We examine these processes in the context of a particular work domain: railroad operations. Analyses revealed a variety of informal cooperative strategies that railroad workers have developed that span across multiple railroad crafts including roadway workers, train crews, and railroad dispatchers. These informal, proactive communications foster shared situation awareness across the distributed organization, facilitate work, and contribute to the overall efficiency, safety, and resilience to error of railroad operations. We discuss design implications for leveraging new digital technologies and location-finding systems to more effectively support these informal strategies, enhance shared situation awareness, and promote high reliability performance.

One of the most limiting factors for distributed sensor networks used for railroad track health monitoring applications is the lack of a long-term, low-maintenance power supply. Most existing systems still require a change of battery, and remoteness of location and low frequency of maintenance can limit their practical deployment. In this paper we describe an investigation of two principal methods for harvesting mechanical power from passing railcars in order to supply electrical power to remote networks of sensors. We first considered an inductive voice coil device directly driven by vertical rail displacement. We then considered a piezoelectric device that is attached to the bottom of the rail and is driven by the longitudinal strain produced by rail bending due to passing railcars. Theoretical models of the behavior of these devices were integrated with an analytical model of rail track deflection to perform numerical simulations of both of these power scavenging techniques. Lab and field tests were also performed to validate the simulation results. Resulting values of average power production show promise for scavenging near the targeted level of 1 mW, and the field data matched well with the simulations.

This study tested whether trait emotional intelligence (TEI) measures of narrow bandwidth predict perception of facial emotion, using two tasks: identification of microexpressions of emotion and controlled visual search for target emotions. A total of 129 undergraduates completed multiple scales for TEI, as well as cognitive ability, personality, and stress measures. TEI was associated with a reduced stress response, but failed to predict performance on either task, contrary to the initial hypothesis. However, performance related significantly to higher cognitive intelligence, subjective task engagement, and use of task-focused coping. Individual differences in attentional resources may support processing of both emotive and non-emotive stimuli.

This article describes a new system for high-speed and noncontact rail integrity evaluation being developed at the University of California at San Diego. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection has been tested at the University of California at San Diego Rail Defect Farm. In addition to a real-time statistical analysis algorithm, the prototype uses a specialized filtering approach due to the inherently poor signal-to-noise ratio of the air-coupled ultrasonic measurements in rail steel. The laboratory results indicate that the prototype is able to detect internal rail defects with a high reliability. Extensions of the system are planned to add rail surface characterization to the internal rail defect detection. In addition to the description of the prototype and test results, numerical analyses of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach algorithm and some of these results are shown. The numerical analysis has helped designing various aspects of the prototype for maximizing its sensitivity to defects.

Misuse cases are a way of modeling negative requirements, that is, behaviors that should not occur in a system. In particular, they can be used to model attacks on a system as well as the security mechanisms needed to avoid them. However, like use cases, misuse cases describe requirements in a high-level and informal manner. This means that, whilst they are easy to understand, they do not lend themselves to testing or analysis. In this paper, we present an executable misuse case modeling language which allows modelers to specify misuse case scenarios in a formal yet intuitive way and to execute the misuse case model in tandem with a corresponding use case model. Misuse scenarios are given in executable form and mitigations are captured using aspect-oriented modeling. The technique is useful for brainstorming potential attacks and their mitigations. Furthermore, the use of aspects allows mitigations to be maintained separately from the core system model. The paper, supported by a UML-based modeling tool, describes an application to two case studies, providing evidence that the technique can support red-teaming of security requirements forn realistic systems.

ABSTRACT: Alicyclobacillus acidoterrestris can produce sufficient guaiacol (methoxyphenol), a metabolic by‐product of the bacterium, in apple juice to cause a detectable taint characterized by an antiseptic off‐odor or distinct medicinal flavor and lingering aftertaste. Bacterial spoilage may not be visibly detectable. The objective of this study was to determine the best estimate threshold (BET) for detection of guaiacol in water and commercial pasteurized apple juice from concentrate using the forced‐choice ascending concentration method of limits with an experienced 17‐member sensory panel. The mean BET for aroma detection of guaiacol in water and apple juice was 0.48 ppb and 0.91 ppb, respectively. The mean BET for taste detection of guaiacol in water and apple juice was 0.17 ppb and 0.24 ppb, respectively. Individual aroma BET values ranged from 0.06 ppb to 4.71 ppb guaiacol in water and 0.17 ppb to 4.71 ppb for guaiacol in apple juice. Individual taste BET values ranged from 0.01 ppb to 4.71 ppb for guaiacol in water and apple juice. The taste BET was equal to or lower than the aroma BET for guaiacol in both water and apple juice for all panelists. There was about a 500‐fold range in guaiacol taste detection between panelists, with some individuals exhibiting a BET value as low as 10 ppt (trillion). The information should be useful for developing quality assurance sensory methodology to evaluate potential apple juice flavor spoilage by Alicyclobacillus spp.

OBJECTIVE: To determine sources and amounts of variation in a kinetics ELISA (KELA) and results of culture of fecal samples for Mycobacterium avium subsp paratuberculosis (MAP) in repeated tests of individual cows. ANIMALS: 112 cows on 6 commercial dairy farms in New York. PROCEDURE: A nonrandom longitudinal study was conducted from January 2001 to March 2002. A KELA was performed monthly, and MAP culture was performed bimonthly. Cow- and herd-level data were collected. The KELA and culture results were analyzed by use of models that corrected for clustering within herds and repeated measures on cows. RESULTS: Cows of second or higher lactation had increased KELA values, compared with values for first-lactation cows. Cows had lowest KELA values during the first 15 days in milk; KELA values increased until 60 days in milk and then stabilized. Moderate and heavy shedders had significantly higher KELA values than culture-negative cows, and KELA values of shedders progressively increased over time. On average, the KELA value was significantly increased 132 days after a cow was first detected to be a moderate shedder and 236 days after a cow was first detected to be a low shedder. CONCLUSIONS AND CLINICAL RELEVANCE: Analysis suggests that KELA results vary on a cow-level on the basis of lactation number and stage of lactation. High KELA values indicate heavy fecal shedding, but the KELA is not useful in identifying low and moderate shedders that can require up to 236 days to have a significant increase in KELA value.

Low carbon baintic steel shows promising potential, especially in critical components such as frogs and switches.Microstructural analysis of J6 bainitic rail steel was performed and compared with the microstructure of premium pearlitic rail steel.The bainitic microstructure revealed a mixture of tempered martensite and ferrite associated with intralath carbides.Typical pearlitic microstructure with a fine lamellar aggregate of very soft and ductile ferrite and very hard carbide cementite was observed.The mechanical properties, plane stress fracture toughness, K I c , and the fatigue crack growth behavior of the two steels were evaluated.Test specimens were machined from railheads of each material using electrical discharge machining (EDM).Rectangular unnotched and notched specimens were used for the mechanical properties and fatigue evaluation respectively.1/2T compact tension specimens were used for the K I c evaluation according to ASTM E399.The J6 bainitic steel has ultimate strength, yield strength, and elongation to failure of about 1500 MPa, 1100 MPa, and 13% respectively.These values are higher than those for pearlitic steel.It was found that the average K I c for the bainitic rail steel is 52 MPa √ m, while that of the premium pearlitic steel is 41 MPa √ m.Fatigue studies showed that the crack speed for the bainitic steel is lower than that for the pearlitic steel over the entire range of the energy release rate.The bainitic steel exhibits a higher rate of crack deceleration in the second stage, as indicated by the lower slope of the fatigue crack propagation kinetics curve in comparison with the pearlitic steel.This attests to the superior fatigue damage tolerance of the bainitic rail steel and provides evidence to support the superior rolling fatigue damage tolerance of the bainitic rail steel reported in the literature.

This article presents findings from projects conducted by the Transportation Technology Center, Inc. concerning track maintenance problems associated with bridge approaches of railway track. Field tests for determining root causes of, and evaluating remedies for, such problems were conducted at the Facility for Accelerated Service Testing near Pueblo, Colorado, and at a number of revenue service sites in the United States. Investigations covered ballast deck concrete bridges with concrete ties, open deck steel bridges with wood ties, and their approaches.

This article assesses the quality and apparent use of regulatory analysis for economically significant regulations proposed by federal agencies in 2008. A nine-member research team used a six-point (0-5) scale to evaluate regulatory analyses according to criteria drawn from Executive Order 12866 and Office of Management and Budget Circular A-4. Principal findings include: (1) the average quality of regulatory analysis, though not high, is somewhat better than previous regulatory scorecards have shown; (2) quality varies widely; (3) biggest strengths are accessibility and clarity; (4) biggest weaknesses are analysis of the systemic problem and retrospective analysis; (5) budget or "transfer" regulations usually receive low-quality analysis; (6) a minority of the regulations contain evidence that the agency used the analysis in significant decisions; (7) quality of analysis is positively correlated with the apparent use of the analysis in regulatory decisions; and (8) greater diffusion of best practices could significantly improve the overall quality of regulatory analysis.

The Office of Safety of the Federal Railroad Administration (FRA) is responsible for ensuring public and personnel safety in U.S. railroad operations. This office ensures the safe rail transportation of hazardous materials by conducting inspections of railroad operations and equipment, including tank cars, and developing safety-related regulations. In the past few years, the Office of Safety has been using risk analysis as a tool in making rational regulatory decisions on hazardous materials transportation in tank cars. A risk analysis protocol developed by FRA is described to evaluate the risks to the U.S. population arising from the transportation of different types of chemicals in tank cars on the U.S. railroad system. Following several recommendations of the National Transportation Safety Board requiring the shipment of several hazardous chemicals in highly protected, pressure-rated tank cars rather than in the minimum packaging authorized by the Code of Federal Regulations, a risk-based evaluation was made on the effect of implementing these recommendations on the overall risk reduction. The risk results were presented in the parameters of Military Standard 882-B. Policy decisions were made based on the results.

The microstructure-properties relationships, fatigue crack growth, and fracture surface morphology of J6 bainitic and premium pearlitic rail steels are studied. Specimens are cut from the middle of each railhead along the longitudinal direction of the rail using electrical discharge machining. Fatigue crack propagation tests are conducted under load control conditions using a servo hydraulic material testing system. A simple form of the fatigue power law is used to rank the fatigue crack growth kinetics of the two materials. The results show that bainitic steel has superior fatigue damage tolerance as represented by the fatigue lifetime, fatigue crack propagation kinetics, and fatigue fracture surface morphological features. Fracture surface analysis of fatigue failed specimens revealed the various mechanisms by which bainitic steel acquired its superior resistance to fatigue crack growth. Bainitic rail steel displayed more ductile fracture features such as tearing, and extensive ridge formation during the stable crack propagation process than pearlitic steel. These features are responsible for the crack deceleration and indicate a considerably high energy consuming process associated with the crack propagation of bainitic steel. Pulled-up pearlitic lamella, limited microcracks, and microvoid coalescence are found on the fracture surface of pearlitic rail steel during the stable crack process. The unstable crack propagation region of bainitic steel exhibits both large and small dimples indicative of high resistance to material separation. On the other hand, cleavage and intergranular separation are associated with the unstable crack region in pearlitic steel.

Ballast fouling is a problematic track condition that can lead to inadequate ballast performance. Prioritizing remediation of fouled ballast sites is difficult because no relationship between ballast fouling and track performance exists and fouled ballast performance depends on the amount, grain-size, type, plasticity, and moisture content of the fouling material. This paper provides results of an international industry survey on fouled ballast definitions, parameters, limits/standards, and laboratory test results to aid development of a procedure for quantitatively assessing ballast fouling and assessing the ability to: transmit applied train loads to the subgrade, allow drainage, and maintain proper track geometry as required under §213.103.

Slender columns subjected to compressive stress are common in many civil structures. The rapid in situ measurement of this stress may prevent structural buckling. In this study, the authors applied an artificial neural network (ANN) to process numerical data that describe the coupling mechanism between highly nonlinear solitary waves (HNSWs) propagating along a granular system and a beam in contact with the granular medium. The aim is to evaluate the ability of HNSWs to measure stress in thermally loaded structures and to estimate the neutral temperature, i.e., the temperature at which the stress is null. Nonlinear solitary waves are compact nondispersive waves that can form and travel in nonlinear systems such as one-dimensional chains of particles, where they are conventionally generated by the mechanical impact of a striker. The authors numerically investigated a straight chain of spherical particles in contact with a prismatic beam subjected to thermal stress. The effect of the neutral temperature on certain features of the waves was examined. These features then were fed into an ANN with the aim of estimating the neutral temperature. In the future, the findings presented in this paper may be used to develop a novel sensing system for the nondestructive prediction of neutral temperature and thermal buckling.

Ballast degradation in the track substructure may cause poor drainage, settlement, and reduced lateral stability that may affect safety, daily operations, and long-term maintenance of a railroad system. Extreme levels of degradation in the ballast may result in service interruptions because of safety concerns. Therefore, field ballast condition evaluation is deemed crucial. Current state-of-the-practice methods for evaluating ballast condition primarily rely on subjective visual inspection, labor-intensive sampling, and laboratory sieve analyses of collected field samples. A network-level condition assessment of ballast and track substructure is commonly performed using ground-penetrating radar. For site-specific and detailed geotechnical analyses, development of a reliable, accurate, and cost-effective technique for ballast condition evaluation is urgently needed. This paper presents an innovative approach to accomplish image-based ballast condition evaluation based on deep learning techniques. A ballast image dataset (library) is established by collecting images from various railroad sites and laboratory setups of ballast piles. A vision transformer-based segmentation framework is implemented and trained with the established dataset and employed to serve as the image segmentation kernel to relate the image-based Percent Degraded Segments (PDS) with the ground-truth Fouling Index (FI). Based on the presented research findings, the proposed approach for field ballast condition evaluation will serve as the core data analysis component of an automated ballast scanning vehicle to conduct field ballast inspection, which is being developed to serve as an efficient and reliable system for the evaluation of ballast condition in ballasted railroad tracks.

Three recent accidents involving the release of hazardous material have focused attention on the structural integrity of railroad tank cars: (1) Minot, ND, on January 18, 2002; (2) Macdona, TX, on June 28, 2004; and (3) Graniteville, SC, on January 6, 2005. Each of these accidents resulted in fatalities. Research is being conducted to develop strategies for improving railroad tank cars so they can maintain tank integrity in severe accidents. A collaborative effort called the Next Generation Rail Tank Car (NGRTC) Project intends to use these research results to help develop improved tank car designs. Dow Chemical Company, Union Pacific Railroad, and Union Tank Car Company are the industry sponsors of the NGRTC Project. The Federal Railroad Administration (FRA) and Transport Canada participate in the NGRTC project through Memoranda of Cooperation. FRA and the Pipeline and Hazardous Materials Safety Administration intend to use these research results to support rulemaking. The approach taken in performing this research is to define the collision conditions of concern, to evaluate the behavior of current design equipment in these scenarios, and to develop alternative strategies for increasing the maximum impact speed for which tank integrity is maintained. The accident scenarios have been developed from a review of accidents and are intended to bound the range of main-line accidents that can lead to a release of hazardous material from a tank car. The accident scenarios and collision modes have been used to define car-to-car impact scenarios. These car-to-car impact scenarios define the conditions under which the commodity must be contained. The impact scenarios are being used to evaluate the integrity of current design and improved design tank cars. Full-scale impact tests are also being conducted, to help validate modeling of the baseline equipment. The models have been refined based on the test results. The models are now being applied to develop the improved equipment designs. This paper describes the overall research framework and provides an overview of the research done to date, as well as the planned efforts.

The most prevalent use of the dispute review board (DRB) process in the United States to date is the central artery/tunnel project located in Boston. A DRB is a three-member panel jointly chosen by the contractor and owner that is present throughout the course of the contract, and whose responsibility it is to hear disputes contemporaneously with their occurrence. This paper reviews the efficacy of the DRB on the central artery/tunnel project answering such questions as to whether or not (1) there was any discernable bid savings between DRB and non-DRB contracts; (2) the DRB was successful in resolving all disputes prior to contract completion; (3) were there any barriers to the DRB’s effectiveness, concerning bid savings; and (4) the DRB reduced the costs of resolving disputes. The questions are timely and important in an industry that looks for new ways to reduce construction costs and values timely prevention and resolution to disputes.

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Broken joint bars have been identified as one of the major causes of main line derailments in the US. On October 2006, the US Federal Railroad Administration issued a federal regulation that mandates periodic inspections to detect cracks and other indications of potential failures in CWR joints [1]. The rule requires periodic on-foot inspection or an approved alternative procedure providing equivalent or higher level of safety. This paper describes a new machine vision-based system for joint bars inspection at speeds up to 70 mph. Four line-scan cameras mounted on a hi-railer or full size rail vehicle continuously capture high resolution images from both sides of each rail. An on-board computer system analyzes these images in real time to detect the joint bars. Each joint bar image is automatically saved and analyzed for visible fatigue cracks. The images can also be analyzed for missing bolts and other defects. When a potential defect is detected, the system provides audio warning, tags the image with GPS position, and displays the joint bar image with highlighted defects on the screen. The operator may confirm or reject defects. At the end of the survey, the operator can generate a survey report with the joint bar GPS location and types of all defects. This new system improves productivity and workers safety, inspecting joint bars from a moving vehicle instead of having to walk along highly transited tracks. It also allows the railroads to reduce the time between inspections, preventing defects to develop into hazards. Several tests have been performed on different rail roads showing system defect detection capabilities on both CWR and jointed track.

A significant portion of railroad infrastructure exists in areas that are relatively remote. Railroad crossings in these areas are typically only marked with reflective signage and do not have warning light systems or crossbars due to the cost of electrical infrastructure. Distributed sensor networks used for railroad track health monitoring applications would be useful in these areas, but the same limitation regarding electrical infrastructure exists. This motivates the search for a long-term, low-maintenance power supply solution for remote railroad deployment. This paper describes the development of a mechanical device for harvesting mechanical power from passing railcar traffic that can be used to supply electrical power to warning light systems at crossings and to remote networks of sensors via rechargeable batteries. The device is mounted to and spans two rail ties such that it directly harnesses the vertical displacement of the rail and attached ties and translates the linear motion into rotational motion. The rotational motion is amplified and mechanically rectified to rotate a PMDC generator that charges a system of batteries. A prototype was built and tested in a laboratory setting for verifying functionality of the design. Results indicate power production capabilities on the order of 10 W per device in its current form. This is sufficient for illuminating high-efficiency LED lights at a railroad crossing or for powering track-health sensor networks.